Posts Tagged ‘ teaching ’

A helpful structure for analysing graphs

April 22, 2014
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A helpful structure for analysing graphs

Mathematicians teaching English “I became a maths teacher so I wouldn’t have to mark essays” “I’m having trouble getting the students to write down their own ideas” “When I give them templates I feel as if it’s spoon-feeding them” These … Continue reading →

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Understanding Simpson’s paradox using a graph

April 8, 2014
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Understanding Simpson’s paradox using a graph

Joshua Vogelstein pointed me to this post by Michael Nielsen on how to teach Simpson’s paradox. I don’t know if Nielsen (and others) are aware that people have developed some snappy graphical methods for displaying Simpson’s paradox (and, more generally, aggregation issues). We do some this in our Red State Blue State book, but before […]The post Understanding Simpson’s paradox using a graph appeared first on Statistical Modeling, Causal Inference,…

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Interpreting noise

April 6, 2014
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Interpreting noise

When watching the TV news, or reading newspaper commentary, I am frequently amazed at the attempts people make to interpret random noise. For example, the latest tiny fluctuation in the share price of a major company is attributed to the CEO being ill. When the exchange rate goes up, the TV finance commentator confidently announces that it is a reaction to Chinese building contracts. No one ever says “The unemployment…

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Just gave a talk

March 31, 2014
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I just gave a talk in Milan. Actually I was sitting at my desk, it was a g+ hangout which was a bit more convenient for me. The audience was a bunch of astronomers so I figured they could handle a satellite link. . . . Anyway, the talk didn’t go so well. Two reasons: […]The post Just gave a talk appeared first on Statistical Modeling, Causal Inference, and Social…

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Teaching Confidence Intervals

March 31, 2014
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Teaching Confidence Intervals

If you want your students to understand just two things about confidence intervals, what would they be? What and what order When making up a teaching plan for anything it is important to think about whom you are teaching, what … Continue reading →

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A statistical graphics course and statistical graphics advice

March 25, 2014
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Dean Eckles writes: Some of my coworkers at Facebook and I have worked with Udacity to create an online course on exploratory data analysis, including using data visualizations in R as part of EDA. The course has now launched at https://www.udacity.com/course/ud651 so anyone can take it for free. And Kaiser Fung has reviewed it. So definitely feel free […]The post A statistical graphics course and statistical graphics advice appeared first on Statistical Modeling,…

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Teaching Bayesian applied statistics to graduate students in political science, sociology, public health, education, economics, . . .

March 20, 2014
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Teaching Bayesian applied statistics to graduate students in political science, sociology, public health, education, economics, . . .

One of the most satisfying experiences for an academic is when someone asks a question that you’ve already answered. This happened in the comments today. Daniel Gotthardt wrote: So for applied stat courses like for sociologists, political scientists, psychologists and maybe also for economics, what do we actually want to accomplish with our intro courses? […]The post Teaching Bayesian applied statistics to graduate students in political science, sociology, public health,…

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The candy weighing demonstration, or, the unwisdom of crowds

March 20, 2014
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From 2008: The candy weighing demonstration, or, the unwisdom of crowds My favorite statistics demonstration is the one with the bag of candies. I’ve elaborated upon it since including it in the Teaching Statistics book and I thought these tips might be useful to some of you. Preparation Buy 100 candies of different sizes and […]The post The candy weighing demonstration, or, the unwisdom of crowds appeared first on Statistical…

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Fast computation of cross-validation in linear models

March 17, 2014
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Fast computation of cross-validation in linear models

The leave-one-out cross-validation statistic is given by     where , are the observations, and is the predicted value obtained when the model is estimated with the th case deleted. This is also sometimes known as the PRESS (Prediction Residual Sum of Squares) statistic. It turns out that for linear models, we do not actually have to estimate the model times, once for each omitted case. Instead, CV can be…

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The silent dog – null results matter too!

March 16, 2014
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The silent dog – null results matter too!

Recently I was discussing the process we use in a statistical enquiry. The ideal is that we start with a problem and follow the statistical enquiry cycle through the steps Problem, Plan, Data collection, Analysis and Conclusion, which then may … Continue reading →

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